The invention relates generally to magnetic sensors, and more particularly to a maneuverable magnetic anomaly sensing system and method that is rotationally invariant and that provides robust magnetic target detection and localization information.
Magnetic sensor technologies are being developed to enhance the capabilities of highly-maneuverable autonomous underwater vehicles (AUVs) and other underwater systems. These underwater systems can include navigation, communications and xe2x80x9cdetection, localization and classificationxe2x80x9d (DLC) of underwater objects/obstructions or buried objects such as cables or mines. Magnetic sensors can detect and use the static and dynamic magnetic anomaly fields that emanate from magnetically polarizable underwater objects to localize/classify the objects. The low frequency magnetic anomaly signals are not affected by water turbulence and multi-path propagation effects that can limit the performance of other underwater sensing technologies.
Practical constraints on magnetic sensor operation aboard small underwater vehicles impose serious technical challenges principally due to the following factors. First, changes in vehicle orientation in the earth""s background magnetic induction field BE of 50,000 nano-Tesla (nT) produces large non-target-related changes in the nT-level vector components measured by onboard vector magnetometers. As is the case for any mobile application of low frequency magnetic sensors, in order to obtain useful detection sensitivity and range, the adverse effects of sensor rotation in the earth""s field must be eliminated or reduced to an acceptable level in the design of the field-sensing element or compensated by means of signal processing software. However, for small underwater vehicles, the adverse effects of sensor motion are exacerbated because their operation typically involves frequent large, nearly random changes in vehicle orientation due to water turbulence and the effects of uneven seafloor structure.
A second factor hampering magnetic sensor operation onboard small underwater vehicles is that the magnetic signatures of a vehicle""s frame, drive motors and other vehicle subsystems may obscure the magnetic signature of a magnetic anomaly which can be indicative of a target object or a communication signal. Hence, in order to achieve effective sensitivity and range, reasonable efforts should be made to reduce the vehicle magnetic signature as much as is practical, to locate the magnetic sensors as far as practical from the magnetically xe2x80x9chotxe2x80x9d sections of the vehicle, and to utilize sensor calibration and signal processing techniques that compensate for the non-target-related fields and gradients that are produced by the vehicle""s self-magnetic signature.
In addition, the vehicle""s limited size and power budget requires the sensing system to be compact, low power and easily portable. The system must combine hardware, software and an efficient target location methodology to optimize the vehicle""s search capabilities. These technical problems are somewhat mitigated by the relatively reduced detection range requirements that are allowed by the operational paradigm of detection, localization and classification of magnetic objects using smart AUVs. In this paradigm, the AUV can adaptively modify its search patterns in response to the detected presence of objects, and, for example, autonomously maneuver (under guidance from an efficient magnetic sensor based homing algorithm) so as to maximize its probability of accurately localizing and classifying an object once it is detected.
A brief review is presented of some relevant physical and mathematical concepts that affect the design, development and use of magnetic sensing technologies. Throughout this disclosure, vector quantities are denoted by boldface letters and scalar quantities by normal type. For example, BA is a vector while BA is a scalar value or quantity. The methodologies and apparatus used for detection, localization and classification of magnetic xe2x80x9canomaliesxe2x80x9d that are produced by magnetic objects are based on and conditioned by:
1) The existence of vector magnetic induction fields BA that emanate from the objects"" net magnetization (characterized as a vector xe2x80x9cmagnetic dipole momentxe2x80x9d M) and,
2) The existence of the relatively large magnetic induction field of the earth BE that permeates all space around the planetary surface.
FIG. 1 presents a simplified qualitative representation of magnetic field lines of force. As designated by the arrowheads in FIG. 1, the (BA) field lines leave one end (i.e., the north pole) of a dipole moment M, and curve around and return to the other end (i.e., the south pole) of dipole moment M. Consequently, in the presence of a nearly constant background field such as BE, the BA field can, depending where the field values are measured, either add to or subtract from BE. At distances, r, from the object that are greater than about three times the object""s largest dimension, the BA fields are described by the well-known magnetic dipole field equation of classical electromagnetic theory. Consequently, the BA fields that are produced by magnetic objects generate rapidly-varying, anomalous changes (i.e., amplitudes are reduced by 1/r3) in the slowly varying earth""s background field BE.
As is well known in the art, the magnitude BE is generally much larger than BA (i.e., BE greater than  greater than BA ) except for field points that are measured very close to the dipole source M of the magnetic object""s anomaly field BA. The earth""s field and anomaly field vectors sum to create a total field BT=BE+BA. The problem of using BA to detect and localize magnetic objects, then, requires methods and apparatus than can detect and discriminate relatively small target signatures BA that are convolved with the relatively very large (yet also fairly constant) earth field BE.
There are, broadly speaking, two separate approaches to magnetic anomaly localization. One approach involves measurement of changes in the scalar field BT and the other approach involves measurement of changes in the vector (and/or tensor) components of BT. Both approaches have their advantages and limitations.
The scalar total field approach typically involves the use of magnetic field sensors or magnetometers (e.g., proton precession magnetometers, atomic vapor magnetometers, etc.) that detect and measure the scalar magnitude of the total field BT. An important advantage of this approach is the fact that true scalar quantities are xe2x80x9crotationally invariantxe2x80x9d, that is, they do not change when the sensor coordinate system rotates. Therefore, scalar magnetometers are often used for mobile applications where the sensor platform can undergo large changes in orientation angle. However, total field magnetometers that can only respond to BT essentially only measure the components of BA that are parallel to BE (i.e., the scalar projection of BA on BE) and therefore cannot provide a complete set of the target localization information that is implicit in BA. In particular, although BT and the embedded anomaly field BA are rotational invariants, they are not by themselves xe2x80x9crobustxe2x80x9d quantities that allow efficient localization of magnetic anomalies. As used herein, the term xe2x80x9crobustxe2x80x9d will be applied to mathematical quantities or signals that always increase as a sensor approaches a target and always decrease as the sensor-target distance increases.
In essence then, true scalar magnetometers do develop rotationally invariant total field signals that contain some target signature information. However, the inherently limited target localization and classification capabilities of scalar total field data require inefficient use of platform mobility resources when trying to find magnetic objects. Specifically, in order to localize magnetic targets, scalar total field magnetometer based sensor systems must make many passes over the target area. Furthermore, unless some form of actual contact with the target is made, there will be ambiguities as to actual target position and size.
The vector approach to magnetic anomaly detection and localization is based on magnetic field sensors (e.g., fluxgates, SQUIDs, magnetoresistive devices and Hall effect devices) with field sensing elements whose output voltages represent the direction and magnitude of field vector along the elements"" sensitive axes. For example, a set of three vector sensors can be configured to form a xe2x80x9ctriaxialxe2x80x9d sensor that has three mutually perpendicular field sensing axes that intersect at a single point so that they form a local orthogonal coordinate system at the local position of the triaxial sensor. In principle, since a set of three non-coplanar vector magnetometers can completely determine the three dimensional field components of BA, the vector magnetometer approach has the advantage that none of the anomaly field""s implicit target localization information is lost. However, any measurement of magnetic anomaly vector components also necessarily includes the much larger in magnitude vector components of the earth""s field BE. Consequently, vector magnetometers actually measure the components of the total field BT=BE+BA along the sensors"" axes of sensitivity so that sensors"" outputs contain BTx, BTy, BTz, where BTx=BEx+BAx, etc. The magnitude and direction of the measured components very strongly depend on the sensor system""s orientation in the earth""s field.
Depending on sensor orientation, the component of the earth""s field BE along any given sensor axis can vary between xc2x150,000 nT. Also, depending on sensor axis orientation, the angular rate of change in measured field component with changes in sensor angular orientation can vary between 0 to xc2x1900 nT/degree. Thus, mobile applications for vector magnetometers are severely limited by the fact that changes in orientation of the measuring sensor can produce non-target related changes in the measured vector components and overwhelm the nT-level and sub-nT-level target signals. For these reasons, the use of vector magnetometers is usually limited to applications where the sensors do not move or where motion of the sensor platform is restricted to straight line tracks. However, such restrictions on sensor motion greatly restrict the range of practical applications for mobile vector sensors.
For mobile applications, triaxial vector sensors can be operated in a total field mode that creates a rotationally invariant scalar total field quantity from measurements of three orthogonal field components (BTx, BTy, BTz) in the sensor""s coordinate system. The rotationally invariant total scalar field is obtained by mathematically combining the field quantities in the expression
BT=(BTx2+BTy2+BTz2)0.5
However, as discussed above, BT is not a very robust quantity and deviations of the sensor axes from perfect orthogonality can again produce non-target related changes in the measured BT that overwhelm small target signals. Still, if the sensor motion errors somehow can be eliminated or greatly reduced, BT can provide very useful indications of the presence of a target somewhere in the detection space of the sensor.
In summary, the vector magnetometer approach has an advantage over the scalar approach in that vector measurements in principle can provide a method for sensitive target detection and accurate localization. However, in practice, the major limitation of the conventional vector magnetometer approach for magnetic target detection and localization from mobile sensor platforms is that the very small BA signals must be discriminated from the larger background BE field.
In order to apply the inherent localization capabilities of vector field sensors to mobile anomaly sensing applications, it is generally necessary to use the sensors in hardware and/or software configurations that essentially only measure the difference in field values between spatially separated points. Then, the gradient components of the magnetic anomaly field are equal to the difference in the field values xcex94B divided by the separation distance measured along the line joining the measurement points. Compared to the direct BA vector field sensing method, use of the gradient of BA, or ∇BA, can result in a reduction of detection range. This is because the amplitudes of the gradient signals are proportional to 1/r4 while the direct BA field components are proportional to 1/r3 where xe2x80x9crxe2x80x9d is the distance between the sensor and the magnetic object. Even so, the gradient approach is attractive because it is, in principle, relatively insensitive to sensor rotations in the earth""s field because the earth""s field gradient is very small.
In practice, however, due to imperfections in their construction and alignment, gradiometers are subject to sensor orientation dependent imbalance errors. Similar to the case of vector magnetometers, the rotation of gradiometer sensors in the earth""s B-field causes non-target related changes in the matrix elements of the gradient tensor and, consequently, sensor rotation-induced degradation of the gradiometer""s detection range. Even in perfectly balanced gradiometers, rotations of the sensor platform will produce changes in the tensor""s matrix elements that can cause the system to lose the magnetic target because of computational complexities brought about by a moving coordinate system.
Owing to errors produced by sensor platform motion, the conventional use of gradiometers for sensing magnetic dipole targets onboard mobile platforms is limited to applications where the sensor system can be moved at constant velocity on a straight line track, with essentially no changes in sensor platform orientation. In addition, the conventional gradient tensor technique involves significant computational overhead that, together with the need to avoid large changes in sensor orientation, impede the practical adaptation of the technique to highly mobile systems such as autonomous robotic vehicles involved in pseudo random search patterns for buried mines.
Accordingly, it is an object of the present invention to provide a magnetic anomaly sensing system.
Another object of the present invention is to provide a magnetic anomaly sensing system that is unaffected by random sensor movement.
Still another object of the present invention is to provide a magnetic anomaly sensing system that performs well on highly maneuverable platforms.
Yet another object of the present invention is to provide a magnetic anomaly sensing system that can robustly detect magnetic anomalies in underwater environments.
A still further object of the present invention is to provide a magnetic anomaly sensing system that operates on passive sensing principles.
Another object of the present invention is to provide a magnetic anomaly sensing system that can be used to detect and locate underwater objects having a magnetic signature.
Other objects and advantages of the present invention will become more obvious hereinafter in the specification and drawings.
In accordance with the present invention, a system and method for sensing magnetic anomalies is provided. A support that is electrically non-conductive and non-magnetic has at least one pair of triaxial magnetometer-accelerometer (TMA) sensors coupled thereto. Each pair of TMA sensors is separated by a known distance. Each TMA sensor has X, Y, Z magnetic sensing axes and X, Y, Z acceleration sensing axes that are, for computational convenience, parallel to one another and to the X, Y, Z magnetic sensing and acceleration axes of all others of the TMA sensors. Each TMA sensor outputs X, Y, Z components (Bx, By, Bz) of local magnetic fields and X, Y, Z components (Ax, Ay, Az) of local gravitational acceleration fields. The X, Y, Z components (Bx, ByBz) and (Ax, Ay, Az) output from each TMA sensor are processed to generate motion-compensated X, Y, Z components (Bcx, Bcy, Bcz) of local magnetic fields. A difference is generated between the motion-compensated X, Y, Z components (Bcx, Ccy, Bcz) for each pair of TMA sensors thereby generating differential vector field components (xcex94Bx, xcex94By, xcex94Bz). For improved accuracy, the differential vector field components (xcex94Bx, xcex94By, xcex94Bz) can be adjusted using the X, Y, Z components (Ax, Ay, Az) of local gravitational acceleration fields and the motion-compensated (X, Y, Z) components (Bcx, Bcy, Bcz) of local magnetic fields in order to compensate for motion of the support. Gradient components Gij are generated using the differential vector field components (xcex94Bx, xcex94By, xcex94Bz) where i={x, y, z} and j={x, y, z}. In general, for each of the X, Y, Z magnetic sensing axes, the gradient components Gij are defined by (xcex94Bx/xcex94j, xcex94By/66 j, xcex94Bz/xcex94j), wherein xcex94j is a distance between the pair of TMA sensors relative to a j-th one of the X, Y, Z magnetic sensing axes. A scalar-quantity gradient contraction defined as       C    2    =            ∑              i        ,        j              ⁢          xe2x80x83        ⁢                  (                  G          ij                )            2      
is generated for each pair of TMA sensors. The gradient contraction C2 is a robust, rotationally-invariant quantity that changes monotonically with proximity to a magnetic target.